Transmission of moving pictures in real-time is employed in several applications like e.g. video conferencing, net meetings, TV broadcasting and video telephony and are becoming more widespread.
These applications require digital cameras and digital camcorders containing electronic image sensors that capture light for processing into a still or video image, respectively. The quality specifications for the image sensors are increasing as the conventional image resolution is becoming larger. The general factor influencing the image quality the most is the image noise. A large level of noise will generally degrade the quality of the images. Noise may result from different processes taking part in the formation of the image. The characteristics of the noise may also be different. There may be certain patterns due to physical processes or the noise may take the form of a more statistical character often somewhat vaguely named as “Gaussian”.
Most of the noise is created in the image sensors. The image sensors usually include an array of photosensitive elements in series with switching elements. Each photosensitive element receives an image of a portion of the scene being imaged. That portion is called a picture element or pixel. The image obtaining elements produce an electrical signal indicative of the image plus a noise component. Various techniques have been used in the art to minimize the noise, to thereby produce an output signal that closely follows the image. There are two primary types of electronic image sensors, charge coupled devices (CCDs) and complimentary metal oxide semiconductor (CMOS) sensors. CCD image sensors have relatively high signal to noise ratios (SNR) that provide quality images. Additionally, CCDs can be fabricated to have pixel arrays that are relatively small while conforming with most camera and video resolution requirements. A pixel is the smallest discrete element of an image. For these reasons, CCDs are used in most commercially available cameras and camcorders.
CMOS sensors are faster and consume less power than CCD devices. Additionally, CMOS fabrication processes are used to make many types of integrated circuits. Consequently, there is a greater abundance of manufacturing capacity for CMOS sensors than CCD sensors.
To date there has not been developed a CMOS sensor that has the same SNR and pixel pitch requirements as commercially available CCD sensors. Pixel pitch is the space between the centers of adjacent pixels. It would be desirable to provide a CMOS sensor that has relatively high SNR while providing a commercially acceptable pixel pitch.
CCD sensors contain pixel arrays that have multiple rows and columns. When capturing first and second images a CCD must read every row from the array for the first image and then every row in the array for the second image. This is a relatively inefficient approach that contains inherent delays in data retrieval. It would be desirable to decrease the time required to retrieve data from the pixel array.
All light sensors in arrays are exposed to noise due to their spatial and discrete nature. Some light photons simply do not hit the sensors, and consequently contribute to the noise picture. Another noise contributor is the quantization of the light captured by the respective sensors. The representation of the pixel values is digital, i.e. discrete, and conversion from analog to digital data also introduce quantization errors. The amounts of these errors depend on the quantization intervals, which in turn depend on the number of digits representing each pixel. In digital cameras this number has to be limited due to limited processing power and memory space.
The generated noise is often large enough to visually degrade the image. It is therefore desirable to be able to reduce the noise level to obtain a subjectively better image.
At the same time, the rate of picture elements (pixels) in a high quality video signal is very large. For a high definition (HD) video signal this may be in the order of 100 mega pixels/s. This means that a noise reduction method must take computational complexity into account and try to make the procedure simple enough to be feasible for real time implementation.